Fuzzy logic based handwritten character recognition

This paper presents an innovative approach called box method for feature extraction for the recognition of handwritten characters. In this approach, the character image is partitioned into a fixed number of sub images called boxes. The features consist of normalized vector distance (/spl gamma/) and angle (/spl alpha/) from each box to a fixed point. The recognition schemes used are back propagation neural network (BPNN) and fuzzy logic. The recognition rate is found to be around 100% with the fuzzy based approach on the standard database.